Proteogenomic characterization of MiT family translocation renal cell carcinoma

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare type of kidney cancer, which is not well characterized. Here we show the comprehensive proteogenomic analysis of tRCC tumors and normal adjacent tissues to elucidate the molecular landscape of this disease. Our study reveals that defective DNA repair plays an important role in tRCC carcinogenesis and progression. Metabolic processes are markedly dysregulated at both the mRNA and protein levels. Proteomic and phosphoproteome data identify mTOR signaling pathway as a potential therapeutic target. Moreover, molecular subtyping and immune infiltration analysis characterize the inter-tumoral heterogeneity of tRCC. Multi-omic integration reveals the dysregulation of cellular processes affected by genomic alterations, including oxidative phosphorylation, autophagy, transcription factor activity, and proteasome function. This study represents a comprehensive proteogenomic analysis of tRCC, providing valuable insights into its biological mechanisms, disease diagnosis, and prognostication.

The exact sample size (n) for each experimental group/condition, given as as a discrete number and unit of of measurement A statement on on whether measurements were taken from distinct samples or or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.
A description of of all covariates tested A description of of any assumptions or or corrections, such as as tests of of normality and adjustment for multiple comparisons A full description of of the statistical parameters including central tendency (e.g. means) or or other basic estimates (e.g. regression coefficient) AND variation (e.g. standard deviation) or or associated estimates of of uncertainty (e.g. confidence intervals) For null hypothesis testing, the test statistic (e.g. F, t, r) with confidence intervals, effect sizes, degrees of of freedom and P value noted Give P values as exact values whenever suitable.
For Bayesian analysis, information on on the choice of of priors and Markov chain Monte Carlo settings For hierarchical and complex designs, identification of of the appropriate level for tests and full reporting of of outcomes Estimates of of effect sizes (e.g. Cohen's d, Pearson's r), ), indicating how they were calculated Our web collection on statistics for biologists contains articles on many of the points above.

Software and code
Policy information about availability of of computer code Data collection Chen Ding, Dingwei Ye, Hailiang Zhang, Jian-Yuan Zhao Oct 25, 2022 Proteome and phosphoproteome samples were analysed on on a Q Exactive HF-X mass spectrometer (Thermo Fisher Scientific, Rockford, IL, USA) coupled with high-performance liquid chromatography (EASY-nLC 1200 System, Thermo Fisher Scientific).The mass spectrometry data were acquired using the Xcalibur software v2.2 (Thermo Fischer Scientific). Whole exome sequencing (WES) were all performed on on the Nextseq CN500 platform (Illumina).

Data analysis
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Portfolio guidelines for submitting code & software for further information.

Data
Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A description of any restrictions on data availability -For clinical datasets or third party data, please ensure that the statement adheres to our policy

Human research participants
Policy information about studies involving human research participants and Sex and Gender in Research.

Reporting on sex and gender
Population characteristics

Recruitment
Ethics oversight Note that full information on the approval of the study protocol must also be provided in the manuscript.

Field-specific reporting
Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences
Behavioural & social sciences Ecological, evolutionary & environmental sciences For WES data, paired-end reads in Fastq format were aligned to a reference human genome (UCSC Genome Browser, hg19) using Burrows-Wheeler Aligner. Variant calling was conducted following GATK best practices. Somatic single-nucleotide variations and small insertions and deletions were detected using MuTect2 (GATK v4.1.2.0) and were annotated using ANNOVAR based on UCSC known genes. CNAs were called following somatic CNA best practice, using the CalculateTargetCoverage function in GATK (v4.1.2.0). RNA-seq reads were mapped onto the human reference genome (GRCh38.p13 assembly) by using STAR software (v2.7.7.a). The mapped reads were assembled into transcripts or genes by using StringTie software (v2. The raw sequencing data are available under controlled access due to data privacy laws related to patient consent for data sharing and the data should be used for research purposes only. Access can be obtained by approval via their respective DAC (Data Access Committees) in the GSA-human database. According to the guidelines of GSA-human, all non-profit researchers are allowed access to the data and the Principle Investigator of any research group is allowed to apply for Controlled-access of the data. The user can register and login to the GSA database website (https://ngdc.cncb.ac.cn/gsa-human/) and follow the guidance of "Request Data" to request the data step by step [https://ngdc.cncb.ac.cn/gsa-human/document/GSA-Human_Request_Guide_for_Users_us.pdf]. The approximate response time for accession requests is about 2 weeks. The access authority can be obtained for Research Use Only. The user can also contact the corresponding author directly. Once access has been granted, the data will be available to download for 3 months. Source data are provided with this paper. The remaining data are available within the Article, Supplementary Information or Source Data file. This cohort was comprised by 33.7% (n =29) males and 66.3% (n = 57) females.
We retrospectively screened all the 3,850 patients who underwent radical or partial nephrectomy for the treatment of renal tumors at Fudan University Shanghai Cancer Center (FUSCC, Shanghai, China), from January 2008 to December 2020, collecting 86 eligible tRCC cases. The retrospective and single-center design of this study also led to several inherent biases, such as selection bias.
The study was compliant with the ethical standards of Helsinki Declaration II and was approved by the institutional review board of FUSCC (050432-4-2108*). Written informed consent was obtained from each patient before any study-specific investigation was conducted.

March 2021
For a reference copy of of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
All studies must disclose on on these points even when the disclosure is is negative. We We screened all the 3,850 consecutive patients who underwent radical or or partial nephrectomy for the treatment of of renal tumors at at FUSCC, one of of the largest cancer centers in in East Asian, from January 2008 to to December 2020, collecting 86 86 eligible tRCC cases. We We collected the cases of of this rare type of of cancer as as much as as possible.
Whole exome sequencing was performed using 86 86 paired samples, except for 2 patients due to to low DNA quality.
All attempts at at replication were successful. The sample sizes are indicated in in the figure legends.
The tRCC samples for multi-omics processing were not randomized, as as investigators were blinded to to clinical information.
For sample processing, PCA, consensus clustering analysis, all investigators were blinded to to clinical information (including TNM stage, ISUP grade, and patients outcomes).
The cell line was tested negtaive for mycoplasma contamination.
No No commonly misidentified cell lines were used.